Social and environmental risk factors for dengue in Delhi city: A retrospective study

Surveillance of mosquitoes harnessing their buzzing sound

Mosquito surveillance for vector-borne disease management relies on traditional morphological and molecular techniques, which are tedious, time-consuming, and costly. The present study describes a simple and efficient recording device that analyzes mosquito sound to estimate species composition, male-female ratio, fed-unfed status, and harmonic convergence interaction using fundamental frequency (F0) bandwidth, harmonics, amplitude, and combinations of these parameters. The study examined a total of 19 mosquito species, including 3 species of Aedes, 7 species of Anopheles, 1 species of Armigeres, 5 species of Culex, 1 species of Hulecoetomyia, and 2 species of Mansonia. Among them, the F0 ranges between 269.09 ± 2.96 Hz (Anopheles culiciformis) to 567.51 ± 3.82 Hz (Aedes vittatus) and the harmonic band (hb) number ranges from 5 (An. culiciformis) to 12 (Ae. albopictus). In terms of species identification, the success rate was 95.32 % with F0, 84.79 % with F0-bandwidth, 84.79 % with harmonic band (hb) diversity, and 49.7 % with amplitude (dB). The species identification rate has gone up to 96.50 % and 97.66 % with the ratio and multiplication of F0 and hb, respectively. This is because of the matrices that combine multiple sound attributes. Comparatively, combinations of the amplitude of the F0 and the higher harmonic frequency band were non-significant for species identification (60.82 %). The fed females have shown a considerable increase in F0 in comparison to the unfed. The males of all the species possessed significantly higher frequencies with respect to the females. Interestingly, the presence of male-female of Ae. vittatus together showed harmonic convergence between the 2nd and 3rd harmonic bands. In conclusion, the sound-based technology is simple, precise, and cost-effective and provides better resolution for species, sex, and fed-unfed status detection in comparison to conventional methods. Real-time surveillance of mosquitoes could potentially utilize this technology.

Exploring Dengue Dynamics: A Multi-Scale Analysis of Spatio-Temporal Trends in Ibagué, Colombia

Our study examines how dengue fever incidence is associated with spatial (demographic and socioeconomic) alongside temporal (environmental) factors at multiple scales in the city of Ibagué, located in the Andean region of Colombia. We used the dengue incidence in Ibagué from 2013 to 2018 to examine the associations with climate, socioeconomic, and demographic factors from the national census and satellite imagery at four levels of local spatial aggregation. We used geographically weighted regression (GWR) to identify the relevant socioeconomic and demographic predictors, and we then integrated them with environmental variables into hierarchical models using integrated nested Laplace approximation (INLA) to analyze the spatio-temporal interactions. Our findings show a significant effect of spatial variables across the different levels of aggregation, including human population density, gas and sewage connection, percentage of woman and children, and percentage of population with a higher education degree. Lagged temporal variables displayed consistent patterns across all levels of spatial aggregation, with higher temperatures and lower precipitation at short lags showing an increase in the relative risk (RR). A comparative evaluation of the models at different levels of aggregation revealed that, while higher aggregation levels often yield a better overall model fit, finer levels offer more detailed insights into the localized impacts of socioeconomic and demographic variables on dengue incidence. Our results underscore the importance of considering macro and micro-level factors in epidemiological modeling, and they highlight the potential for targeted public health interventions based on localized risk factor analyses. Notably, the intermediate levels emerged as the most informative, thereby balancing spatial heterogeneity and case distribution density, as well as providing a robust framework for understanding the spatial determinants of dengue.

Automatic mapping of high-risk urban areas for Aedes aegypti infestation based on building facade image analysis

BACKGROUND

Dengue, Zika, and chikungunya, whose viruses are transmitted mainly by Aedes aegypti, significantly impact human health worldwide. Despite the recent development of promising vaccines against the dengue virus, controlling these arbovirus diseases still depends on mosquito surveillance and control. Nonetheless, several studies have shown that these measures are not sufficiently effective or ineffective. Identifying higher-risk areas in a municipality and directing control efforts towards them could improve it. One tool for this is the premise condition index (PCI); however, its measure requires visiting all buildings. We propose a novel approach capable of predicting the PCI based on facade street-level images, which we call PCINet.

METHODOLOGY

Our study was conducted in Campinas, a one million-inhabitant city in São Paulo, Brazil. We surveyed 200 blocks, visited their buildings, and measured the three traditional PCI components (building and backyard conditions and shading), the facade conditions (taking pictures of them), and other characteristics. We trained a deep neural network with the pictures taken, creating a computational model that can predict buildings' conditions based on the view of their facades. We evaluated PCINet in a scenario emulating a real large-scale situation, where the model could be deployed to automatically monitor four regions of Campinas to identify risk areas.

PRINCIPAL FINDINGS

PCINet produced reasonable results in differentiating the facade condition into three levels, and it is a scalable strategy to triage large areas. The entire process can be automated through data collection from facade data sources and inferences through PCINet. The facade conditions correlated highly with the building and backyard conditions and reasonably well with shading and backyard conditions. The use of street-level images and PCINet could help to optimize Ae. aegypti surveillance and control, reducing the number of in-person visits necessary to identify buildings, blocks, and neighborhoods at higher risk from mosquito and arbovirus diseases.

Spatial analysis of food and water-borne diseases in Ahmedabad, India: Implications for urban public health planning

Spatial analysis of infectious diseases can play an important role in mapping the spread of diseases and can support policy making at local level. Moreover, identification of disease clusters based on local geography and landscape forms the basis for disease control and prevention. Therefore, this study aimed to examine the spatial-temporal variations, hotspot areas, and potential risk factors of infectious diseases (including Viral Hepatitis, Typhoid and Diarrhea) in Ahmedabad city of India. We used Moran's I and Local Indicators of Spatial Association (LISA) mapping to detect spatial clustering of diseases. Spatial and temporal regression analysis was used to identify the association between disease incidence and spatial risk factors. The Moran's I statistics identified presence of positive spatial autocorrelation within the considered diseases, with Moran's I from 0.09 for typhoid to 0.21 for diarrhea (p < 0.001). This indicates a clustering of affected wards for each disease, suggesting that cases were not randomly distributed across the city. LISA mapping demonstrated the clustering of hotspots in central regions of the city, especially towards the east of the river Sabarmati, highlighting key geographical areas with elevated disease risk. The spatial clusters of infectious diseases were consistently associated with slum population density and illiteracy. Furthermore, temporal analysis suggested illiteracy rates could increase risk of viral hepatitis by 13 % (95 % Confidence Interval (CI): 1.01-1.26) and of diarrhea by 18 % (95 % CI: 1.07-1.31). Significant inverse association was also seen between viral hepatitis incidence and the distance of wards from rivers. Conclusively, the study highlight the impact of socio-economic gradients, such as slum population density (indicative of poverty) and illiteracy, on the localized transmission of water and foodborne infections. The evident social stratification between impoverished and affluent households emerges as a notable contributing factor and a potential source of differences in the dynamics of infectious diseases in Ahmedabad.

Interactions between climate change, urban infrastructure and mobility are driving dengue emergence in Vietnam

Dengue is expanding globally, but how dengue emergence is shaped locally by interactions between climatic and socio-environmental factors is not well understood. Here, we investigate the drivers of dengue incidence and emergence in Vietnam, through analysing 23 years of district-level case data spanning a period of significant socioeconomic change (1998-2020). We show that urban infrastructure factors (sanitation, water supply, long-term urban growth) predict local spatial patterns of dengue incidence, while human mobility is a more influential driver in subtropical northern regions than the endemic south. Temperature is the dominant factor shaping dengue's distribution and dynamics, and using long-term reanalysis temperature data we show that warming since 1950 has expanded transmission risk throughout Vietnam, and most strongly in current dengue emergence hotspots (e.g., southern central regions, Ha Noi). In contrast, effects of hydrometeorology are complex, multi-scalar and dependent on local context: risk increases under either short-term precipitation excess or long-term drought, but improvements in water supply mitigate drought-associated risks except under extreme conditions. Our findings challenge the assumption that dengue is an urban disease, instead suggesting that incidence peaks in transitional landscapes with intermediate infrastructure provision, and provide evidence that interactions between recent climate change and mobility are contributing to dengue's expansion throughout Vietnam.

Knowledge, attitude and practice (KAP) and risk factors on dengue fever among children in Brazil, Fortaleza: A cross-sectional study

BACKGROUND

Dengue fever is a mosquito-borne viral disease that is associated with four serotypes of the dengue virus. Children are vulnerable to infection with the dengue virus, particularly those who have been previously infected with a different dengue serotype. Sufficient knowledge, positive attitudes, and proper practices (KAP) are essential for dengue prevention and control. This study aims to estimate the dengue seropositivity for study participants and to examine the association between households' dengue-related knowledge, attitudes, and practices (KAP), and children's risk of dengue seropositivity, while accounting for socioeconomic and demographic differences in Brazil.

METHODOLOGY/PRINCIPAL FINDINGS

This analysis was based on a cross-sectional study from Fortaleza, Brazil between November 2019, and February 2020. There were 392 households and 483 participant children who provided a sample of sufficient quality for serological analysis. The main exposure was a household's dengue-related knowledge, attitudes, and practices, assessed through a questionnaire to construct a composite KAP score categorized into three levels: low, moderate, and high. The main outcome is dengue immunoglobulin G(IgG) antibodies, collected using dried blood spots and assessed with Panbio Dengue IgG indirect ELISA (enzyme-linked immunosorbent assays) test commercial kits. The estimated crude dengue seroprevalence among participating children (n = 483) was 25%. Five percent of households (n = 20) achieved a score over 75% for KAP, sixty-nine percent of households (n = 271) scored between 50% and 75%, and twenty-six percent of households (n = 101) scored lower than 50%. Each KAP domain was significantly and positively associated with the others. The mean percentage scores for the three domains are 74%, 63%, and 39% respectively. We found high household KAP scores were associated with an increased adjusted relative risk (aRR) of seropositivity (aRR: 2.11, 95% CI: 1.11-4.01, p = 0.023). Household adult respondents' education level of elementary school or higher was negatively associated with children's risk of being seropositive (aRR: 0.65, 95% CI: 0.48-0.87, p = 0.005). The risk of seropositivity in older children (6-12 years old) was over 6 times that of younger children (2-5 years old) (aRR: 6.08, 95% CI: 3.47-10.64, p<0.001). Children living in households with sealed water tanks or no water storage had a lower risk of being seropositive (aRR: 0.73, 95% CI: 0.54-0.98, p = 0.035).

CONCLUSIONS/SIGNIFICANCE

Our results provide insight into the prevalence of dengue seropositivity in Fortaleza, Brazil in children, and certain demographic and socioeconomic characteristics associated with children's risk of being seropositive. They also suggest that KAP may not identify those more at-risk for dengue, although understanding and enhancing households' KAP is crucial for effective community dengue control and prevention initiatives.

The mismatch of narratives and local ecologies in the everyday governance of water access and mosquito control in an urbanizing community

Mosquito-borne disease presents a significant threat to urban populations, but risk can be uneven across a city due to underlying environmental patterns. Urban residents rely on social and economic processes to control the environment and mediate disease risk, a phenomenon known as everyday governance. We studied how households employed everyday governance of urban infrastructure relevant to mosquito-borne disease in Bengaluru, India to examine if and how inequalities in everyday governance manifest in differences in mosquito control. We found that governance mechanisms differed for water access and mosquitoes. Economic and social capital served different roles for each, influenced by global narratives of water and vector control.

Relationship between Urban Environmental Components and Dengue Prevalence in Dhaka City-An Approach of Spatial Analysis of Satellite Remote Sensing, Hydro-Climatic, and Census Dengue Data

Dengue fever is a tropical viral disease mostly spread by the Aedes aegypti mosquito across the globe. Each year, millions of people have dengue fever, and many die as a result. Since 2002, the severity of dengue in Bangladesh has increased, and in 2019, it reached its worst level ever. This research used satellite imagery to determine the spatial relationship between urban environmental components (UEC) and dengue incidence in Dhaka in 2019. Land surface temperature (LST), urban heat-island (UHI), land-use-land-cover (LULC), population census, and dengue patient data were evaluated. On the other hand, the temporal association between dengue and 2019 UEC data for Dhaka city, such as precipitation, relative humidity, and temperature, were explored. The calculation indicates that the LST in the research region varies between 21.59 and 33.33 degrees Celsius. Multiple UHIs are present within the city, with LST values ranging from 27 to 32 degrees Celsius. In 2019, these UHIs had a higher incidence of dengue. NDVI values between 0.18 and 1 indicate the presence of vegetation and plants, and the NDWI identifies waterbodies with values between 0 and 1. About 2.51%, 2.66%, 12.81%, and 82% of the city is comprised of water, bare ground, vegetation, and settlement, respectively. The kernel density estimate of dengue data reveals that the majority of dengue cases were concentrated in the city's north edge, south, north-west, and center. The dengue risk map was created by combining all of these spatial outputs (LST, UHI, LULC, population density, and dengue data) and revealed that UHIs of Dhaka are places with high ground temperature and lesser vegetation, waterbodies, and dense urban characteristics, with the highest incidence of dengue. The average yearly temperature in 2019 was 25.26 degrees Celsius. May was the warmest month, with an average monthly temperature of 28.83 degrees Celsius. The monsoon and post-monsoon seasons (middle of March to middle of September) of 2019 sustained higher ambient temperatures (>26 °C), greater relative humidity (>80%), and at least 150 mm of precipitation. The study reveals that dengue transmits faster under climatological circumstances characterized by higher temperatures, relative humidity, and precipitation.

Efficacy Assessment of Autodissemination Using Pyriproxyfen-Treated Ovitraps in the Reduction of Dengue Incidence in Parañaque City, Philippines: A Spatial Analysis

Dengue is one of the most important vector-borne diseases worldwide and is a significant public health problem in the tropics. Mosquito control continues to be the primary approach to reducing the disease burden and spread of dengue virus (DENV). Aside from the traditional larviciding and adulticiding interventions, autodissemination using pyriproxyfen-treated (AD-PPF) ovitraps is one of the promising methods to complement existing vector control strategies. Our paper assessed the efficacy of AD-PPF in reducing DENV infections in two barangays in Parañaque City. Using saliva samples from the participants from both the control and intervention sites, we collected the seroprevalence data for three months in each of the two years. Spatial analysis was conducted to determine hotspot areas and identify DENV infection distributions across the trial periods. The results showed that the intervention site was identified as having a clustering of DENV infections in Month 0 of Year 1 and shifted to a random dispersion of dengue cases at the end of Month 3 in Year 2. The disappearance of the clustering of the intervention site translates to a decrease in the cases of DENV infection relative to the control site. Furthermore, we also identified that DENV transmission occurred at a small-scale level that did not go beyond 86 m. In conclusion, AD-PPF is suggested to be an effective strategy and may be used as an additional vector control approach, albeit based on this short-term implementation.

Why is leptospirosis hard to avoid for the impoverished? Deconstructing leptospirosis transmission risk and the drivers of knowledge, attitudes, and practices in a disadvantaged community in Salvador, Brazil

Several studies have identified socioeconomic and environmental risk factors for infectious disease, but the relationship between these and knowledge, attitudes, and practices (KAP), and more importantly their web of effects on individual infection risk, have not previously been evaluated. We conducted a cross-sectional KAP survey in an urban disadvantaged community in Salvador, Brazil, leveraging on simultaneously collected fine-scale environmental and epidemiological data on leptospirosis transmission. Residents' knowledge influenced their attitudes which influenced their practices. However, different KAP variables were driven by different socioeconomic and environmental factors; and while improved KAP variables reduced risk, there were additional effects of socioeconomic and environmental factors on risk. For example, males and those of lower socioeconomic status were at greater risk, but once we controlled for KAP, male gender and lower socioeconomic status themselves were not direct drivers of seropositivity. Employment was linked to better knowledge and a less contaminated environment, and hence lower risk, but being employed was independently associated with a higher, not lower risk of leptospirosis transmission, suggesting travel to work as a high risk activity. Our results show how such complex webs of influence can be disentangled. They indicate that public health messaging and interventions should take into account this complexity and prioritize factors that limit exposure and support appropriate prevention practices.

Dengue risk zone mapping of Thiruvananthapuram district, India: a comparison of the AHP and F-AHP methods

Dengue fever, which is spread by Aedes mosquitoes, has claimed many lives in Kerala, with the Thiruvananthapuram district bearing the brunt of the toll. This study aims to demarcate the dengue risk zones in Thiruvananthapuram district using the analytical hierarchy process (AHP) and the fuzzy-AHP (F-AHP) methods. For the risk modelling, geo-environmental factors (normalized difference vegetation index, land surface temperature, topographic wetness index, land use/land cover types, elevation, normalized difference built-up index) and demographic factors (household density, population density) have been utilized. The ArcGIS 10.8 and ERDAS Imagine 8.4 software tools have been used to derive the risk zone maps. The area of the risk maps is classified into five zones. The dengue risk zone maps were validated using dengue case data collected from the Integrated Disease Surveillance Programme portal. From the receiver operating characteristic (ROC) curve analysis and the area under the ROC curve (AUC) values, it is proved that the F-AHP method (AUC value of 0.971) has comparatively more prediction capability than the AHP method (AUC value of 0.954) in demarcating the dengue risk zones. Also, based on the comparison of the risk zone map with actual case data, it was confirmed that around 82.87% of the dengue cases occurred in the very high and high-risk zones, thus proving the efficacy of the model. According to the dengue risk map prepared using the F-AHP model, 9.09% of the area of Thiruvananthapuram district is categorized as very high risk. The prepared dengue risk maps will be helpful for decision-makers, staff with the health, and disaster management departments in adopting effective measures to prevent the risks of dengue spread and thereby minimize loss of life.

Effective Infection with Dengue Virus in Experimental Neonate and Adult Mice through the Intranasal Route

Dengue virus, the causative agent of dengue fever, life-threatening hemorrhagic fever, and shock syndrome, is mainly transmitted to humans through mosquito vectors. It can also be transmitted through atypical routes, including needle stick injury, vertical transmission, blood transfusion, and organ transplantation. In addition, sporadic cases which have no clear infectious causes have raised the respiratory exposure concerns, and the risks remain unclear. Here, we analyze the respiratory infectivity of the dengue virus in BALB/c suckling and adult immunodeficient mice by the intranasal inoculation of dengue virus serotype 2. The infected mice presented with clinical symptoms, including excitement, emaciation, malaise, and death. Viremia was detected for 3 days post inoculation. Histopathological changes were observed in the brain, liver, and spleen. The virus showed evident brain tropism post inoculation and viral loads peaked at 7 days post inoculation. Furthermore, the virus was isolated from the infected mice; the sequence homology between the origin and isolates was 99.99%. Similar results were observed in adult IFN-α/β receptor-deficient mice. Overall, dengue virus can infect suckling mice and adult immune-deficient mice via the nasal route. This study broadens our perception of atypical dengue transmission routes and provides evidence of nasal transmission of dengue virus in the absence of mosquito vectors.

Social and housing indicators of dengue and chikungunya in Indian adults aged 45 and above: Analysis of a nationally representative survey (2017-18)

Background

Dengue and chikungunya (CHIKV) are the two major vector-borne diseases of serious public health concern in India. Studies on socioeconomic and housing determinants of dengue and CHIKV at a pan-India level are lacking. Here, we took advantage of the recently carried out Longitudinal Ageing Study in India (LASI) carried out across all the states and Union Territories of India to study the social indicators of dengue and CHIKV in India.

Methods

LASI-1 (2017-2018) data on the self-reported period prevalence of dengue and CHIKV from 70,932 respondents aged ≥45 years were used for this analysis. The state-wise distribution of dengue and CHIKV was mapped. Prevalence was estimated for each study variable, and the difference was compared using the χ2 test. The adjusted odds ratios (AOR) of the socioeconomic and housing variables for dengue and CHIKV were estimated using the multiple logistic regression model.

Results

Urban residence is the major socio-economic indicator of dengue and CHIKV (dengue AOR: 1.57, 95% CI: 1.18-2.11; CHIKV AOR: 1.84, 95% CI: 1.36-2.49). The other notable indicator is wealth; rich respondents have higher odds of dengue and CHIKV. Adults older than 54 years and those with high school education and above are associated with a lower likelihood of dengue and CHIKV. In addition, CHIKV is associated with scheduled and forward castes, households with improper toilet facilities, open defecation, and kutcha house type.

Conclusions

Despite the limitation that the data is only from adults ≥ 45, this analysis provides important insights into the socioeconomic and housing variables associated with higher odds of dengue and CHIKV in India. Understanding these determinants may assist in the national planning of prevention and control strategies for dengue and CHIKV.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-022-00868-5.

Community Knowledge and Attitudes about the Transmission of Dengue Haemorrhagic Fever and Its Relationship to Prevention Behaviour in Palembang, South Sumatra, Indonesia

BACKGROUND: PSN 3 M Plus is a long-running program in Indonesia for the prevention and control of dengue hemorrhagic fever (DHF). AIM: This study aimed to determine the knowledge, behavior, attitudes, and beliefs of the community toward PSN 3 M Plus in preventing and controlling the spread of DHF. METHODS: A cluster random sampling method was used to recruit 200 respondents in endemic areas and 100 respondents in sporadic locations of Indonesia from August 2020 to February 2021. The respondents were interviewed directly by interviewers and the relationships between demographics and characteristics with the practice of PSN 3M Plus prevention behavior on the incidence of DHF were analyzed. RESULTS: Most respondents had good knowledge regarding the cause of DHF. Although respondents recognized and understood the dangers of and how to control DHF, most did not follow PSN 3 M Plus and believed that fogging was the most effective control measure. There was a significant relationship between the characteristics of the respondents in terms of education, occupation, and attitude on vector control practice. CONCLUSION: Although community environmental modifications can be a cost-effective approach to reduce the incidence of DHF, there is a need to raise public awareness regarding preventive vector control measures as good knowledge does not guarantee good compliance with PSN 3M Plus recommendations.

Integrating Spatial Modelling and Space-Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan

The spatial–temporal assessment of vector diseases is imperative to design effective action plans and establish preventive strategies. Therefore, such assessments have potential public health planning-related implications. In this context, we here propose an integrated spatial disease evaluation (I-SpaDE) framework. The I-SpaDE integrates various techniques such as the Kernel Density Estimation, the Optimized Hot Spot Analysis, space–time assessment and prediction, and the Geographically Weighted Regression (GWR). It makes it possible to systematically assess the disease concentrations, patterns/trends, clustering, prediction dynamics, and spatially varying relationships between disease and different associated factors. To demonstrate the applicability and effectiveness of the I-SpaDE, we apply it in the second largest city of Pakistan, namely Lahore, using Dengue Fever (DF) during 2007–2016 as an example vector disease. The most significant clustering is evident during the years 2007–2008, 2010–2011, 2013, and 2016. Mostly, the clusters are found within the city’s central functional area. The prediction analysis shows an inclination of DF distribution from less to more urbanized areas. The results from the GWR show that among various socio-ecological factors, the temperature is the most significantly associated with the DF followed by vegetation and built-up area. While the results are important to understand the DF situation in the study area and have useful implications for public health planning, the proposed framework is flexible, replicable, and robust to be utilized in other similar regions, particularly in developing countries in the tropics and sub-tropics.

Successful Outpatient Management of Children at a Secondary Care Hospital in Pakistan in a Dengue Fever Epidemic and Their Clinical Outcomes

Background

There is limited published literature on the feasibility of WHO 2009 guidelines for the management of dengue fever (DF) in Pakistani children. This study aimed to assess the outcome of children with DF who received outpatient treatment according to these guidelines during a DF epidemic.

Method

This was a prospective cohort study conducted at Federal General Hospital, a secondary care hospital, Islamabad, Pakistan, from 1st August to 31st October 2019. Using WHO DF 2009 guidelines, children ≤13 years, diagnosed as confirmed DF (NS1 Ag +), were classified into the outpatient (DF) or the inpatient group (DF with warning signs or severe dengue (SD)). The inpatient group was admitted to the Pakistan Institute of Medical Sciences, a tertiary care hospital, and discharged on recovery. These children were followed for the primary outcome, i.e., recovery or hospitalization by day 14 of enrollment. Additionally, clinical and laboratory features (Hb, HCT, TLC, PLT, and ALT) of the patients in the outpatient who remained stable with those who progressed to inpatient care during follow-up were compared; also, time of recovery of blood counts was assessed.

Results

Of 93 children with DF, 87 (93.5%) received outpatient care at enrollment. Of these, 6 (7.8%) deteriorated by day 7 and were admitted to inpatient care. SD was present in 6/93 (6.4%) patients at presentation and were admitted. All children showed signs of recovery until day 14. Male gender (p=0.049), lower normal mean platelet (p=0.02), and high mean hematocrit (p=0.001) were associated with disease progression.

Conclusion

The majority of children with confirmed DF who received outpatient treatment according to WHO 2009 guidelines were successfully managed. Additionally, confirmed DF with warning signs or SD were admitted and recovered. Regular follow-ups according to the guidelines are pertinent. Thrombocytopenia and high HCT were associated with disease progression.

"We Tried to Borrow Money, but No One Helped." Assessing the Three-Delay Model Factors Affecting the Healthcare Service Delivery among Dengue Patients during COVID-19 Surge in a Public Tertiary Hospital: A Convergent Parallel Mixed Methods Study

Identification of delay barriers to care is essential for an effective and efficient healthcare service delivery. In this study, we described the delay in care among parents of the patients seeking treatment for dengue. We also examined the factors affecting the severity of dengue (dengue with warning signs; severe dengue). A convergent parallel design mixed-method approach using Key Informant Interviews (KII) and a survey guided by the Three-Delay Model were conducted among 24 respondents at the National Children’s Hospital (NCH). Coding and thematic analysis using NVIVO and bivariable generalized linear models with a Poisson distribution and robust variance were utilized to analyze the KII transcripts and survey data, respectively. Results showed that financial constraints and previous dengue infection (first delay), mode of transportation, traffic density, and location (second delay), and hospital capacity (third delay) influenced the overall delay uncertainty in seeking care treatment for dengue infection. Furthermore, our bivariable analysis showed that travel time to NCH and place of residency, service given from previous health facilities, and parents’ educational background were associated and played a role in the severity of dengue infection. Interventions focused on the identified factors contributing to delayed care should be made to avoid unwanted clinical outcomes.

Development and Comparison of Dengue Vulnerability Indices Using GIS-Based Multi-Criteria Decision Analysis in Lao PDR and Thailand

Dengue is a continuous health burden in Laos and Thailand. We assessed and mapped dengue vulnerability in selected provinces of Laos and Thailand using multi-criteria decision approaches. An ecohealth framework was used to develop dengue vulnerability indices (DVIs) that explain links between population, social and physical environments, and health to identify exposure, susceptibility, and adaptive capacity indicators. Three DVIs were constructed using two objective approaches, Shannon's Entropy (SE) and the Water-Associated Disease Index (WADI), and one subjective approach, the Best-Worst Method (BWM). Each DVI was validated by correlating the index score with dengue incidence for each spatial unit (district and subdistrict) over time. A Pearson's correlation coefficient (r) larger than 0.5 and a p-value less than 0.05 implied a good spatial and temporal performance. Spatially, DVIWADI was significantly correlated on average in 19% (4-40%) of districts in Laos (mean r = 0.5) and 27% (15-53%) of subdistricts in Thailand (mean r = 0.85). The DVISE was validated in 22% (12-40%) of districts in Laos and in 13% (3-38%) of subdistricts in Thailand. The DVIBWM was only developed for Laos because of lack of data in Thailand and was significantly associated with dengue incidence on average in 14% (0-28%) of Lao districts. The DVIWADI indicated high vulnerability in urban centers and in areas with plantations and forests. In 2019, high DVIWADI values were observed in sparsely populated areas due to elevated exposure, possibly from changes in climate and land cover, including urbanization, plantations, and dam construction. Of the three indices, DVIWADI was the most suitable vulnerability index for the study area. The DVIWADI can also be applied to other water-associated diseases, such as Zika and chikungunya, to highlight priority areas for further investigation and as a tool for prevention and interventions.

Challenges to Mitigating the Urban Health Burden of Mosquito-Borne Diseases in the Face of Climate Change

Cities worldwide are facing ever-increasing pressure to develop mitigation strategies for all sectors to deal with the impacts of climate change. Cities are expected to house 70% of the world's population by 2050, and developing related resilient health systems is a significant challenge. Because of their physical nature, cities' surface temperatures are often substantially higher than that of the surrounding rural areas, generating the so-called Urban Heat Island (UHI) effect. Whilst considerable emphasis has been placed on strategies to mitigate against the UHI-associated negative health effects of heat and pollution in cities, mosquito-borne diseases have largely been ignored. However, the World Health Organization estimates that one of the main consequences of global warming will be an increased burden of mosquito-borne diseases, many of which have an urban facet to their epidemiology and thus the global population exposed to these pathogens will steadily increase. Current health mitigation strategies for heat and pollution, for example, may, however, be detrimental for mosquito-borne diseases. Implementation of multi-sectoral strategies that can benefit many sectors (such as water, labor, and health) do exist or can be envisaged and would enable optimal use of the meagre resources available. Discussion among multi-sectoral stakeholders should be actively encouraged.